add_bin_labels |
Reverse numeric conversion of binary vector |
add_missingness |
Apply MAR missingness to data |
coalesce_one_hot |
Coalesce one-hot encoding back to a single variable |
col_minmax |
Scale numeric vector between 0 and 1 |
combine |
Estimate and combine regression models from multiply-imputed data |
complete |
Impute missing values using imputation model |
convert |
Pre-process data for Midas imputation |
delete_rMIDAS_env |
Delete the rMIDAS Environment and Configuration |
import_midas |
Instantiate Midas class |
midas_setup |
Manually set up Python connection |
mid_py_setup |
Configure python for MIDAS imputation |
na_to_nan |
Replace NA missing values with NaN |
overimpute |
Perform overimputation diagnostic test |
python_configured |
Check whether Python is capable of executing example code |
python_init |
Initialise connection to Python |
reset_rMIDAS_env |
Reset the rMIDAS Environment Configuration |
set_python_env |
Manually select python binary |
skip_if_no_numpy |
Skip test where 'numpy' not available. |
train |
Train an imputation model using Midas |
undo_minmax |
Reverse minmax scaling of numeric vector |